AIMC Topic: Drug Interactions

Clear Filters Showing 91 to 100 of 277 articles

GCHN-DTI: Predicting drug-target interactions by graph convolution on heterogeneous networks.

Methods (San Diego, Calif.) Sep 1, 2022
Determining the interaction of drug and target plays a key role in the process of drug development and discovery. The calculation methods can predict new interactions and speed up the process of drug development. In recent studies, the network-based ...
Neural Networks, Computer Drug Development Drug Interactions
View on PubMed DOI

Multitype drug interaction prediction based on the deep fusion of drug features and topological relationships.

PloS one Aug 29, 2022
Drug-drug interaction (DDI) prediction has received considerable attention from industry and academia. Most existing methods predict DDIs from drug attributes or relationships with neighbors, which does not guarantee that informative drug embeddings ...
Neural Networks, Computer Pharmaceutical Preparations Drug Interactions
View on PubMed DOI

IMSE: interaction information attention and molecular structure based drug drug interaction extraction.

BMC bioinformatics Aug 14, 2022
BACKGROUND: Extraction of drug drug interactions from biomedical literature and other textual data is an important component to monitor drug-safety and this has attracted attention of many researchers in healthcare. Existing works are more pivoted ar...
Neural Networks, Computer Molecular Structure Drug Interactions Data Mining Attention
View on PubMed DOI

A Comprehensive Review of Computational Methods For Drug-Drug Interaction Detection.

IEEE/ACM transactions on computational biology and bioinformatics Aug 8, 2022
The detection of drug-drug interactions (DDIs) is a crucial task for drug safety surveillance, which provides effective and safe co-prescriptions of multiple drugs. Since laboratory researches are often complicated, costly and time-consuming, it's ur...
Machine Learning Databases, Factual Natural Language Processing Drug Interactions Data Mining
View on PubMed DOI

Matrix factorization with denoising autoencoders for prediction of drug-target interactions.

Molecular diversity Jul 23, 2022
Drug-target interaction is crucial in the discovery of new drugs. Computational methods can be used to identify new drug-target interactions at low costs and with reasonable accuracy. Recent studies pay more attention to machine-learning methods, ran...
Machine Learning Algorithms Research Design ROC Curve Drug Interactions
View on PubMed DOI

Does adding the drug-drug similarity to drug-target interaction prediction methods make a noticeable improvement in their efficiency?

BMC bioinformatics Jul 14, 2022
Predicting drug-target interactions (DTIs) has become an important bioinformatics issue because it is one of the critical and preliminary stages of drug repositioning. Therefore, scientists are trying to develop more accurate computational methods fo...
Machine Learning Algorithms Computational Biology Drug Repositioning Drug Interactions
View on PubMed DOI

A Drug Recommendation Model Based on Message Propagation and DDI Gating Mechanism.

IEEE journal of biomedical and health informatics Jul 1, 2022
Drug recommendation task based on the deep learning model has been widely studied and applied in the health care field in recent years. However, the accuracy of drug recommendation models still needs to be improved. In addition, the existing recommen...
Humans Neural Networks, Computer Bayes Theorem Drug Interactions
View on PubMed DOI

SGFNNs: Signed Graph Filtering-based Neural Networks for Predicting Drug-Drug Interactions.

Journal of computational biology : a journal of computational molecular cell biology Jun 20, 2022
Neural Networks, Computer Drug Discovery Drug Interactions Semantics
View on PubMed DOI

Drug-target interaction prediction using reliable negative samples and effective feature selection methods.

Journal of pharmacological and toxicological methods Jun 20, 2022
Machine learning-based approaches in the field of drug discovery have dramatically reduced the time and cost of the laboratory process of detecting potential drug-target interactions (DTIs). Standard binary classifiers require both positive and negat...
Machine Learning Algorithms Drug Discovery Drug Interactions
View on PubMed DOI

Multi-type feature fusion based on graph neural network for drug-drug interaction prediction.

BMC bioinformatics Jun 10, 2022
BACKGROUND: Drug-Drug interactions (DDIs) are a challenging problem in drug research. Drug combination therapy is an effective solution to treat diseases, but it can also cause serious side effects. Therefore, DDIs prediction is critical in pharmacol...
Humans Neural Networks, Computer Drug Interactions Drug-Related Side Effects and Adverse Reactions Gene Fusion
View on PubMed DOI
Popular Topics
Recent Journals